Spread spectrum communication system is widely used nowadays. The spread spectrum or the pseudo-random (PN) code modulation can reduce the interference from other users and wireless signals. During the cross-correlation process of received signals and PN sequence, when the interference is narrow-band signals, the interference signals will spread to the entire band and thus weaken the impact of the interference. As a result, the spread spectrum signals can weaken the narrow-band interference to some extend.
A typical spectrum of a spread spectrum signal (e.g. performing spread spectrum from PN sequence) is submerged in the noise as shown in FIG. 1. An ideal signal is the signal energy that is actually sent out by the mobile station and the noise is the additive interference. Obviously, the ideal signal energy of the spread spectrum is usually less than the noise energy. “Strong interference” generally refers to the blocking signals or the signals that are sent by TV, wireless station and nearby communication equipments. “Typical interference” refers to the signals sent by those low-power sources, such as amateur radio. Processing gain represents the interference signal levels tolerable by the spread signals in mobile stations. The spread signals can still be recovered when they are affected by the typical interference, but they will never be recovered when the strong interference shows up. What's more, even with the typical interference, the signals can be recovered but the system performance will degrade.
Before utilizing CDMA communication system, the frequency band will be swept in order to protect the CDMA signals from the interference of narrow-band signals. However, since some burst signals are hard to be fully forbidden due to the burst characteristic, the narrow-band interference will present disorder and randomicity. The narrow-band interference will increase the congestion rate and call-dropping rate in a CDMA system, as well as overload the radio-frequency power control system, increase the power consumption of mobile station, and reduce base station coverage. Under extreme situation, the high-power interference will even block the entire cell, and thus the normal communication will stop. As a result, we must find a good solution in order to eliminate the impact of the narrow-band interference signals pushing on the CDMA signals and guarantee a good communication quality.
Generally, the methods for dealing with narrow-band interference are divided into two categories:
The first category is to make the signal (usually under analog processing) pass through a narrow-band notch filter or a filter group. This method is usually realized by the surface acoustic technology, which makes estimation for the frequency of interference signals and places the narrow-band notch filter wherever the narrow-band interference signals exist based on the estimation result. (PLL (Phase Locked Loop) can also be used to track the narrow-band interference signals). However, the analog technology has its own limitations, and usually lacks flexibility.
Another category is frequency domain elimination which is generally realized through digital processing. Signals are first digitized and then transformed into frequency domain through Fourier Transform. These data will be processed in the frequency domain and finally be transformed back into the time domain to be output through inverse-Fourier Transform. The methods for processing interference signals in the frequency domain can be concluded into two categories: the first method is to filter out the interference impact through the filter on the frequency domain data and this method is suitable to the case that the bandwidth and location of the interference are already known, but this method will have a certain limitation when the location of the interference in the frequency domain, the bandwidth and the number of the interference are hard to identify, since there is a certain degree of difficulty in designing a fully adaptive filter.
Another method is to compute the signal amplitude on each frequency point and then compare them with a threshold value. The signals exceeding the threshold values will be set as zero or be degraded to noise level. This method can adaptively process multiple narrow-band interferences, multiple interference bandwidths and interference frequency changes. However this method only processes the data that exceed the threshold, and in a practical system, the part of the frequency spectrum with interference will leak to the neighbor frequency points because of some factors such as the selection for the number of the points of Fourier Transform. If the impact of spectrum leakage on the capability for suppressing narrow-band interference is totally ignored, as the result, the capability for suppressing narrow-band interference can not meet the requirements of the system.